Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations2968
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory301.4 KiB
Average record size in memory104.0 B

Variable types

Numeric12

Alerts

avg_basket_size is highly overall correlated with gross_revenue and 1 other fieldsHigh correlation
avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with avg_unique_basket_sizeHigh correlation
avg_unique_basket_size is highly overall correlated with avg_ticket and 1 other fieldsHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
gross_revenue is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qty_invoices is highly overall correlated with gross_revenue and 3 other fieldsHigh correlation
qty_items is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qty_products is highly overall correlated with avg_unique_basket_size and 3 other fieldsHigh correlation
recency_days is highly overall correlated with qty_invoicesHigh correlation
avg_ticket is highly skewed (γ1 = 25.15677718)Skewed
frequency is highly skewed (γ1 = 24.8769082)Skewed
qty_returns is highly skewed (γ1 = 26.84619429)Skewed
customer_id has unique valuesUnique
recency_days has 33 (1.1%) zerosZeros
qty_returns has 1481 (49.9%) zerosZeros

Reproduction

Analysis started2024-08-09 14:05:36.032703
Analysis finished2024-08-09 14:06:03.682503
Duration27.65 seconds
Software versionydata-profiling vv4.9.0
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

UNIQUE 

Distinct2968
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15270.377
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-09T11:06:03.853476image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12619.35
Q113798.75
median15220.5
Q316768.5
95-th percentile17964.65
Maximum18287
Range5940
Interquartile range (IQR)2969.75

Descriptive statistics

Standard deviation1719.1445
Coefficient of variation (CV)0.11258036
Kurtosis-1.2061782
Mean15270.377
Median Absolute Deviation (MAD)1489
Skewness0.032193711
Sum45322479
Variance2955457.9
MonotonicityNot monotonic
2024-08-09T11:06:04.078281image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17850 1
 
< 0.1%
12670 1
 
< 0.1%
17734 1
 
< 0.1%
14905 1
 
< 0.1%
16103 1
 
< 0.1%
14626 1
 
< 0.1%
14868 1
 
< 0.1%
18246 1
 
< 0.1%
17115 1
 
< 0.1%
16611 1
 
< 0.1%
Other values (2958) 2958
99.7%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18277 1
< 0.1%
18276 1
< 0.1%
18274 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18269 1
< 0.1%

gross_revenue
Real number (ℝ)

HIGH CORRELATION 

Distinct2953
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2691.263
Minimum6.2
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-09T11:06:04.300134image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile229.7325
Q1570.845
median1083.905
Q32306.905
95-th percentile7169.562
Maximum279138.02
Range279131.82
Interquartile range (IQR)1736.06

Descriptive statistics

Standard deviation10113.975
Coefficient of variation (CV)3.7580775
Kurtosis399.25289
Mean2691.263
Median Absolute Deviation (MAD)671.49
Skewness17.664809
Sum7987668.7
Variance1.0229249 × 108
MonotonicityNot monotonic
2024-08-09T11:06:04.516829image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1078.96 2
 
0.1%
2053.02 2
 
0.1%
331 2
 
0.1%
1353.74 2
 
0.1%
889.93 2
 
0.1%
745.06 2
 
0.1%
379.65 2
 
0.1%
2092.32 2
 
0.1%
731.9 2
 
0.1%
734.94 2
 
0.1%
Other values (2943) 2948
99.3%
ValueCountFrequency (%)
6.2 1
< 0.1%
13.3 1
< 0.1%
15 1
< 0.1%
36.56 1
< 0.1%
45 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
136263.72 1
< 0.1%
124564.53 1
< 0.1%
116725.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%
65019.62 1
< 0.1%

recency_days
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct272
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.31031
Minimum0
Maximum373
Zeros33
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-09T11:06:05.031409image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median31
Q381
95-th percentile242
Maximum373
Range373
Interquartile range (IQR)70

Descriptive statistics

Standard deviation77.760314
Coefficient of variation (CV)1.2091423
Kurtosis2.7765932
Mean64.31031
Median Absolute Deviation (MAD)26
Skewness1.7980702
Sum190873
Variance6046.6664
MonotonicityNot monotonic
2024-08-09T11:06:05.263334image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.3%
4 87
 
2.9%
2 85
 
2.9%
3 85
 
2.9%
8 76
 
2.6%
10 67
 
2.3%
9 66
 
2.2%
7 66
 
2.2%
17 64
 
2.2%
22 55
 
1.9%
Other values (262) 2218
74.7%
ValueCountFrequency (%)
0 33
 
1.1%
1 99
3.3%
2 85
2.9%
3 85
2.9%
4 87
2.9%
5 43
1.4%
7 66
2.2%
8 76
2.6%
9 66
2.2%
10 67
2.3%
ValueCountFrequency (%)
373 2
0.1%
372 4
0.1%
371 1
 
< 0.1%
368 1
 
< 0.1%
366 4
0.1%
365 2
0.1%
364 1
 
< 0.1%
360 1
 
< 0.1%
359 1
 
< 0.1%
358 4
0.1%

qty_invoices
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7230458
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-09T11:06:05.499232image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile17
Maximum206
Range205
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.8485429
Coefficient of variation (CV)1.5461248
Kurtosis189.99723
Mean5.7230458
Median Absolute Deviation (MAD)2
Skewness10.741904
Sum16986
Variance78.296712
MonotonicityNot monotonic
2024-08-09T11:06:05.720619image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 785
26.4%
3 498
16.8%
4 393
13.2%
5 237
 
8.0%
1 190
 
6.4%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 70
 
2.4%
11 54
 
1.8%
Other values (47) 332
11.2%
ValueCountFrequency (%)
1 190
 
6.4%
2 785
26.4%
3 498
16.8%
4 393
13.2%
5 237
 
8.0%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 70
 
2.4%
10 54
 
1.8%
ValueCountFrequency (%)
206 1
< 0.1%
198 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

qty_items
Real number (ℝ)

HIGH CORRELATION 

Distinct1669
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1579.6698
Minimum1
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-09T11:06:05.942488image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile101.35
Q1296
median638
Q31398.25
95-th percentile4403.25
Maximum196844
Range196843
Interquartile range (IQR)1102.25

Descriptive statistics

Standard deviation5700.0984
Coefficient of variation (CV)3.6084113
Kurtosis518.2266
Mean1579.6698
Median Absolute Deviation (MAD)419
Skewness18.7615
Sum4688460
Variance32491122
MonotonicityNot monotonic
2024-08-09T11:06:06.191662image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 11
 
0.4%
150 9
 
0.3%
88 9
 
0.3%
134 8
 
0.3%
272 8
 
0.3%
288 8
 
0.3%
84 8
 
0.3%
260 8
 
0.3%
246 8
 
0.3%
200 7
 
0.2%
Other values (1659) 2884
97.2%
ValueCountFrequency (%)
1 1
< 0.1%
2 2
0.1%
12 2
0.1%
16 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
23 1
< 0.1%
25 1
< 0.1%
ValueCountFrequency (%)
196844 1
< 0.1%
79879 1
< 0.1%
77373 1
< 0.1%
69993 1
< 0.1%
64549 1
< 0.1%
64124 1
< 0.1%
62812 1
< 0.1%
58243 1
< 0.1%
57772 1
< 0.1%
50255 1
< 0.1%

qty_products
Real number (ℝ)

HIGH CORRELATION 

Distinct469
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.7035
Minimum1
Maximum7837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-09T11:06:06.431566image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q129
median67
Q3135
95-th percentile382
Maximum7837
Range7836
Interquartile range (IQR)106

Descriptive statistics

Standard deviation269.2812
Coefficient of variation (CV)2.1945681
Kurtosis354.34185
Mean122.7035
Median Absolute Deviation (MAD)44
Skewness15.67683
Sum364184
Variance72512.365
MonotonicityNot monotonic
2024-08-09T11:06:06.674114image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 46
 
1.5%
20 38
 
1.3%
35 35
 
1.2%
15 33
 
1.1%
29 32
 
1.1%
19 32
 
1.1%
11 32
 
1.1%
26 31
 
1.0%
18 30
 
1.0%
27 30
 
1.0%
Other values (459) 2629
88.6%
ValueCountFrequency (%)
1 6
 
0.2%
2 14
0.5%
3 15
0.5%
4 17
0.6%
5 26
0.9%
6 29
1.0%
7 18
0.6%
8 19
0.6%
9 27
0.9%
10 27
0.9%
ValueCountFrequency (%)
7837 1
< 0.1%
5586 1
< 0.1%
5095 1
< 0.1%
4577 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1636 1
< 0.1%

avg_ticket
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2965
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.989799
Minimum2.1505882
Maximum4453.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-09T11:06:06.912871image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum2.1505882
5-th percentile4.915888
Q113.118111
median17.936066
Q324.882907
95-th percentile90.052125
Maximum4453.43
Range4451.2794
Interquartile range (IQR)11.764796

Descriptive statistics

Standard deviation119.53254
Coefficient of variation (CV)3.6233182
Kurtosis812.9555
Mean32.989799
Median Absolute Deviation (MAD)5.9616373
Skewness25.156777
Sum97913.724
Variance14288.028
MonotonicityNot monotonic
2024-08-09T11:06:07.134776image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 2
 
0.1%
4.162 2
 
0.1%
14.47833333 2
 
0.1%
18.15222222 1
 
< 0.1%
13.92736842 1
 
< 0.1%
36.24411765 1
 
< 0.1%
29.78416667 1
 
< 0.1%
22.8792623 1
 
< 0.1%
20.51104167 1
 
< 0.1%
149.025 1
 
< 0.1%
Other values (2955) 2955
99.6%
ValueCountFrequency (%)
2.150588235 1
< 0.1%
2.4325 1
< 0.1%
2.462371134 1
< 0.1%
2.511241379 1
< 0.1%
2.515333333 1
< 0.1%
2.65 1
< 0.1%
2.656931818 1
< 0.1%
2.707598253 1
< 0.1%
2.760621572 1
< 0.1%
2.770464191 1
< 0.1%
ValueCountFrequency (%)
4453.43 1
< 0.1%
3202.92 1
< 0.1%
1687.2 1
< 0.1%
952.9875 1
< 0.1%
872.13 1
< 0.1%
841.0214493 1
< 0.1%
651.1683333 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%
615.75 1
< 0.1%

avg_recency_days
Real number (ℝ)

HIGH CORRELATION 

Distinct290
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.045822
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-09T11:06:07.351967image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q125
median48
Q385
95-th percentile200.65
Maximum366
Range365
Interquartile range (IQR)60

Descriptive statistics

Standard deviation63.574954
Coefficient of variation (CV)0.9482314
Kurtosis4.9077055
Mean67.045822
Median Absolute Deviation (MAD)26
Skewness2.0672634
Sum198992
Variance4041.7748
MonotonicityNot monotonic
2024-08-09T11:06:07.588860image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35 49
 
1.7%
14 45
 
1.5%
46 43
 
1.4%
21 43
 
1.4%
22 43
 
1.4%
38 42
 
1.4%
17 41
 
1.4%
27 41
 
1.4%
28 41
 
1.4%
26 41
 
1.4%
Other values (280) 2539
85.5%
ValueCountFrequency (%)
1 17
0.6%
2 15
0.5%
3 19
0.6%
4 27
0.9%
5 18
0.6%
6 21
0.7%
7 31
1.0%
8 24
0.8%
9 27
0.9%
10 27
0.9%
ValueCountFrequency (%)
366 1
 
< 0.1%
365 1
 
< 0.1%
363 1
 
< 0.1%
362 1
 
< 0.1%
357 2
0.1%
356 1
 
< 0.1%
355 2
0.1%
352 1
 
< 0.1%
351 2
0.1%
350 3
0.1%

frequency
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1224
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.11382338
Minimum0.0054495913
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-09T11:06:07.818977image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0088935048
Q10.016339869
median0.025898352
Q30.049426591
95-th percentile1
Maximum17
Range16.99455
Interquartile range (IQR)0.033086722

Descriptive statistics

Standard deviation0.40822067
Coefficient of variation (CV)3.5864395
Kurtosis989.06742
Mean0.11382338
Median Absolute Deviation (MAD)0.012196886
Skewness24.876908
Sum337.82779
Variance0.16664411
MonotonicityNot monotonic
2024-08-09T11:06:08.059038image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 198
 
6.7%
0.0625 17
 
0.6%
0.02777777778 17
 
0.6%
0.02380952381 16
 
0.5%
0.08333333333 15
 
0.5%
0.09090909091 15
 
0.5%
0.03448275862 14
 
0.5%
0.02941176471 14
 
0.5%
0.01923076923 13
 
0.4%
0.02564102564 13
 
0.4%
Other values (1214) 2636
88.8%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
3 1
 
< 0.1%
2 6
 
0.2%
1.142857143 1
 
< 0.1%
1 198
6.7%
0.75 1
 
< 0.1%
0.6666666667 3
 
0.1%
0.550802139 1
 
< 0.1%
0.5308310992 1
 
< 0.1%
0.5 3
 
0.1%

qty_returns
Real number (ℝ)

SKEWED  ZEROS 

Distinct172
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.984164
Minimum0
Maximum9014
Zeros1481
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-09T11:06:08.295894image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q36
95-th percentile62.65
Maximum9014
Range9014
Interquartile range (IQR)6

Descriptive statistics

Standard deviation228.65147
Coefficient of variation (CV)9.1518557
Kurtosis912.13278
Mean24.984164
Median Absolute Deviation (MAD)1
Skewness26.846194
Sum74153
Variance52281.494
MonotonicityNot monotonic
2024-08-09T11:06:08.516341image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
49.9%
1 295
 
9.9%
3 169
 
5.7%
6 93
 
3.1%
2 87
 
2.9%
4 71
 
2.4%
5 43
 
1.4%
12 43
 
1.4%
8 40
 
1.3%
7 38
 
1.3%
Other values (162) 608
20.5%
ValueCountFrequency (%)
0 1481
49.9%
1 295
 
9.9%
2 87
 
2.9%
3 169
 
5.7%
4 71
 
2.4%
5 43
 
1.4%
6 93
 
3.1%
7 38
 
1.3%
8 40
 
1.3%
9 36
 
1.2%
ValueCountFrequency (%)
9014 1
< 0.1%
4824 1
< 0.1%
4027 1
< 0.1%
2302 2
0.1%
1776 1
< 0.1%
1608 1
< 0.1%
1589 1
< 0.1%
1515 1
< 0.1%
1278 1
< 0.1%
1242 1
< 0.1%

avg_unique_basket_size
Real number (ℝ)

HIGH CORRELATION 

Distinct1009
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.158128
Minimum1
Maximum299.70588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-09T11:06:08.730860image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.4021531
Q110
median17.2
Q327.75
95-th percentile56.9475
Maximum299.70588
Range298.70588
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation19.512566
Coefficient of variation (CV)0.88060535
Kurtosis27.705366
Mean22.158128
Median Absolute Deviation (MAD)8.2
Skewness3.4995256
Sum65765.325
Variance380.74025
MonotonicityNot monotonic
2024-08-09T11:06:08.958500image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 54
 
1.8%
14 40
 
1.3%
11 38
 
1.3%
9 33
 
1.1%
18 33
 
1.1%
1 32
 
1.1%
20 31
 
1.0%
10 30
 
1.0%
16 29
 
1.0%
17 28
 
0.9%
Other values (999) 2620
88.3%
ValueCountFrequency (%)
1 32
1.1%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
0.1%
1.5 7
 
0.2%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 24
0.8%
ValueCountFrequency (%)
299.7058824 1
< 0.1%
259 1
< 0.1%
203.5 1
< 0.1%
148 1
< 0.1%
145 1
< 0.1%
136.125 1
< 0.1%
135.5 1
< 0.1%
127 1
< 0.1%
122 1
< 0.1%
118 1
< 0.1%

avg_basket_size
Real number (ℝ)

HIGH CORRELATION 

Distinct1973
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean235.83169
Minimum1
Maximum6009.3333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-09T11:06:09.180902image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44
Q1103.2375
median172
Q3281.375
95-th percentile598.345
Maximum6009.3333
Range6008.3333
Interquartile range (IQR)178.1375

Descriptive statistics

Standard deviation283.87459
Coefficient of variation (CV)1.2037169
Kurtosis102.86589
Mean235.83169
Median Absolute Deviation (MAD)82.625
Skewness7.7098453
Sum699948.45
Variance80584.784
MonotonicityNot monotonic
2024-08-09T11:06:09.406173image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
114 10
 
0.3%
82 9
 
0.3%
73 9
 
0.3%
86 9
 
0.3%
75 8
 
0.3%
136 8
 
0.3%
140 8
 
0.3%
60 8
 
0.3%
88 8
 
0.3%
Other values (1963) 2880
97.0%
ValueCountFrequency (%)
1 2
0.1%
2 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
6009.333333 1
< 0.1%
4282 1
< 0.1%
3906 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2801 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%
2082.225806 1
< 0.1%

Interactions

2024-08-09T11:06:01.048127image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:36.624682image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:38.789190image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:40.869448image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:43.496137image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:45.412394image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:47.847051image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:49.971013image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:51.975839image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:54.588493image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:57.015919image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:58.964415image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:01.224031image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:36.787449image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:38.947422image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:41.089947image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:43.651562image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:45.586021image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:48.022551image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:50.127393image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:52.152040image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:54.759297image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:57.183745image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:59.125989image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:01.394042image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:36.942639image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:39.106775image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:41.443583image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:43.806562image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:45.753304image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:48.191327image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:50.297185image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:52.373845image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:54.929416image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:57.339213image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:59.291736image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:01.574354image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:37.113578image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:39.276959image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:41.621631image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:43.971033image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:45.936193image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:48.371732image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:50.490247image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:52.571396image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:55.107650image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:57.526819image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:59.483560image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:01.734960image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:37.304945image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:39.430779image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:41.778491image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:44.116505image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:46.165869image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:48.527183image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:50.635608image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:52.767063image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:55.265105image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:57.673022image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:59.637685image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:01.925192image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:37.494947image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:39.609736image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:41.958518image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:44.286531image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:46.353800image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:48.708001image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:50.807027image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:52.956262image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:55.710367image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:57.844388image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:59.818365image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:02.113905image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:37.809630image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:39.787029image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:42.151177image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:44.453307image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:46.539674image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:48.884680image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:50.973428image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:53.180814image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:55.962149image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:58.012460image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:00.024714image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:02.279056image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:37.964558image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:39.939737image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:42.352685image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:44.623182image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:46.701838image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:49.039303image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:51.140184image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:53.502469image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:56.123860image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:58.153455image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:00.179179image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:02.463423image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:38.137192image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:40.111251image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:42.671012image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:44.782483image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:46.879255image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:49.214648image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:51.322953image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:53.790887image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:56.310430image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:58.320398image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:00.354354image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:02.641943image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:38.306649image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:40.281699image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:42.986050image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:44.944647image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:47.062900image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:49.391586image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:51.502607image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:54.089907image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:56.491304image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:58.489763image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:00.531900image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:02.800768image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:38.458316image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:40.437652image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:43.144984image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:45.093806image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:47.233838image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:49.615960image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:51.646930image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:54.248784image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:56.671974image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:58.647472image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:00.691257image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:02.973127image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:38.623203image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:40.629266image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:43.320560image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:45.255049image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:47.425916image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:49.791571image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:51.816718image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:54.417578image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:56.844093image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:05:58.809100image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-09T11:06:00.863974image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Correlations

2024-08-09T11:06:09.579856image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
avg_basket_sizeavg_recency_daysavg_ticketavg_unique_basket_sizecustomer_idfrequencygross_revenueqty_invoicesqty_itemsqty_productsqty_returnsrecency_days
avg_basket_size1.000-0.0780.1880.450-0.1230.0280.5750.1010.7290.3850.209-0.097
avg_recency_days-0.0781.000-0.1230.0490.019-0.880-0.251-0.262-0.231-0.167-0.3930.110
avg_ticket0.188-0.1231.000-0.611-0.1300.0910.2460.0610.168-0.3760.1970.048
avg_unique_basket_size0.4500.049-0.6111.000-0.006-0.0730.2920.0250.3220.6990.007-0.108
customer_id-0.1230.019-0.130-0.0061.000-0.002-0.0760.026-0.0700.013-0.0640.001
frequency0.028-0.8800.091-0.073-0.0021.0000.0910.0780.0810.0350.2350.018
gross_revenue0.575-0.2510.2460.292-0.0760.0911.0000.7720.9270.7460.359-0.415
qty_invoices0.101-0.2620.0610.0250.0260.0780.7721.0000.7180.6900.283-0.503
qty_items0.729-0.2310.1680.322-0.0700.0810.9270.7181.0000.7320.334-0.407
qty_products0.385-0.167-0.3760.6990.0130.0350.7460.6900.7321.0000.227-0.436
qty_returns0.209-0.3930.1970.007-0.0640.2350.3590.2830.3340.2271.000-0.114
recency_days-0.0970.1100.048-0.1080.0010.018-0.415-0.503-0.407-0.436-0.1141.000

Missing values

2024-08-09T11:06:03.224044image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-08-09T11:06:03.546463image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgross_revenuerecency_daysqty_invoicesqty_itemsqty_productsavg_ticketavg_recency_daysfrequencyqty_returnsavg_unique_basket_sizeavg_basket_size
017850.05391.21372.034.01733.0297.018.15222235.017.00000021.08.73529450.970588
113047.03232.5956.09.01390.0171.018.90403527.00.0283026.019.000000154.444444
212583.06705.382.015.05028.0232.028.90250023.00.04032350.015.466667335.200000
313748.0948.2595.05.0439.028.033.86607192.00.0179210.05.60000087.800000
415100.0876.00333.03.080.03.0292.0000008.00.07317122.01.00000026.666667
515291.04623.3025.014.02102.0102.045.32647123.00.04011527.07.285714150.142857
614688.05630.877.021.03621.0327.017.21978618.00.057221281.015.571429172.428571
717809.05411.9116.012.02057.061.088.71983635.00.03352041.05.083333171.416667
815311.060767.900.091.038194.02379.025.5434644.00.243316231.026.142857419.714286
916098.02005.6387.07.0613.067.029.93477647.00.0243900.09.57142987.571429
customer_idgross_revenuerecency_daysqty_invoicesqty_itemsqty_productsavg_ticketavg_recency_daysfrequencyqty_returnsavg_unique_basket_sizeavg_basket_size
562617727.01060.2515.01.0645.066.016.0643946.01.0000006.066.0645.000000
563617232.0421.522.02.0203.036.011.70888912.00.1538460.018.0101.500000
563717468.0137.0010.02.0116.05.027.4000004.00.4000000.02.558.000000
564813596.0697.045.02.0406.0166.04.1990367.00.2500000.083.0203.000000
565414893.01237.859.02.0799.073.016.9568492.00.6666670.036.5399.500000
565812479.0473.2011.01.0382.030.015.7733334.01.00000034.030.0382.000000
567914126.0706.137.03.0508.015.047.0753333.00.75000050.05.0169.333333
568513521.01092.391.03.0733.0435.02.5112414.00.3000000.0145.0244.333333
569515060.0301.848.04.0262.0120.02.5153331.02.0000000.030.065.500000
571412558.0269.967.01.0196.011.024.5418186.01.000000102.011.0196.000000